Davi0k · June 23, 2020 10:49
diff --git a/remove-background-from-image.py b/remove-background-from-image.py
 import cv2, argparse # pip install opencv-python argparse
 import numpy as np # pip install numpy

 BLUR = 21
 CANNY_THRESH = (10, 200)
 MASK_DILATE_ITER, MASK_ERODE_ITER = 10, 10
 MASK_COLOR = (0.0, 0.0, 1.0)

 def remove_background_from_image(image: str, output: str) -> None:
    """
 	Removes the Background of an Image that falls within a certain shade of gray.
 		
        Parameters:
            image (str): The path of the image to be processed
            output (str): The path and name of the file with which to save the final result
 	"""

    img = cv2.imread(image)

    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

    edges = cv2.Canny(gray, CANNY_THRESH[0], CANNY_THRESH[1])
    edges = cv2.dilate(edges, None); edges = cv2.erode(edges, None)

    contour_info = list()
    
    contours, note = cv2.findContours(edges, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE)

    for c in contours:
        contour_info.append((
            c,
            cv2.isContourConvex(c),
            cv2.contourArea(c),
        ))

    contour_info = sorted(contour_info, key=lambda c: c[2], reverse=True)

    max_contour = contour_info[0]

    mask = np.zeros(edges.shape)
    
    cv2.fillConvexPoly(mask, max_contour[0], 255)

    mask = cv2.dilate(mask, None, iterations=MASK_DILATE_ITER)
    mask = cv2.erode(mask, None, iterations=MASK_ERODE_ITER)
    mask = cv2.GaussianBlur(mask, (BLUR, BLUR), 0)

    mask_stack = np.dstack([mask] * 3)    

    mask_stack = mask_stack.astype('float32') / 255.0          

    img = img.astype('float32') / 255.0                

    masked = (mask_stack * img) + ((1 - mask_stack) * MASK_COLOR) 

    masked = (masked * 255).astype('uint8')     

    red, green, blue = cv2.split(img)

    result = cv2.merge((red, green, blue, mask.astype('float32') / 255.0))

    cv2.imwrite(output, result * 255)

 if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Add some information about the convertion...")

    parser.add_argument("image", nargs=1, help="Insert the path of the image you want to convert...")

    parser.add_argument("-o", "--output", type=str, help="Insert a valid name for the converted image...", required=False, default="result.png")

    arguments = parser.parse_args()

    remove_background_from_image(arguments.image[0], arguments.output)

    print("The image has been converted successfully, the background has been removed...")
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